Over 60 recipes to achieve a robust and advanced backup and recovery solution leveraging SCDPM Key Features *Adapt to the modern data center design challenges and improve storage efficiency *Effective recipes to help you create your own robust architectural designs *Solve data protection and recovery problems in your organization Book Description System Center Data Protection Manager (SCDPM) is a robust enterprise backup and recovery system that contributes to your BCDR strategy by facilitating the backup and recovery of enterprise data. With an increase in data recovery and protection problems faced in organizations, it has become important to keep data safe and recoverable. This book contains recipes that will help you upgrade to SCDPM and it covers the advanced features and functionality of SCDPM. This book starts by helping you install SCDPM and then moves on to post-installation and management tasks. You will come across a lot of useful recipes that will help you recover your VMware and Hyper-V VMs. It will also walk you through tips for monitoring SCDPM in different scenarios. Next, the book will also offer insights into protecting windows workloads followed by best practices on SCDPM. You will also learn to back up your Azure Stack Infrastructure using Azure Backup. You will also learn about recovering data from backup and implementing disaster recovery. Finally, the book will show you how to configure the protection groups to enable online protection and troubleshoot Microsoft Azure Backup Agent. What you will learn *Install and prepare SQL Server for the SCDPM database *Reduce backup storage with SCDPM and data deduplication *Learn about the prerequisites for supported Hyper-V Server protection *Integrate SCDPM with other System Center products to build optimal services *Protect and restore the SCDPM database *Protect your data center by integrating SCDPM with Azure Backup *Manually create online recovery points and recover production data from Azure *Protect and learn about the requirements to recover Azure Stack with SCDPM Who this book is for If you are an SCDPM administrator, this book will help you verify your knowledge and provide you with everything you need to know about the new release of System Center Data Protection Manager.

Over 90 recipes to help you write clean code, solve common JavaScript problems, and work on popular use cases like SPAs, microservices, native mobile development with Node, React, React Native and Electron. Key Features *Over 90 practical recipes to help you write clean and maintainable JavaScript codes with the latest ES8 *Leverage the power of leading web frameworks like Node and React to build modern web apps *Features comprehensive coverage of tools and techniques needed to create multi-platform apps with JavaScript Book Description JavaScript has evolved into a language that you can use on any platform. Modern JavaScript Web Development Cookbook is a perfect blend of solutions for traditional JavaScript development and modern areas that developers have lately been exploring with JavaScript. This comprehensive guide teaches you how to work with JavaScript on servers, browsers, mobile phones and desktops. You will start by exploring the new features of ES8. You will then move on to learning the use of ES8 on servers (with Node.js), with the objective of producing services and microservices and dealing with authentication and CORS. Once you get accustomed to ES8, you will learn to apply it to browsers using frameworks, such as React and Redux, which interact through Ajax with services. You will then understand the use of a modern framework to develop the UI. In addition to this, development for mobile devices with React Native will walk you through the benefits of creating native apps, both for Android and iOS. Finally, you’ll be able to apply your new-found knowledge of server-side and client-side tools to develop applications with Electron. What you will learn *Use the latest features of ES8 and learn new ways to code with JavaScript *Develop server-side services and microservices with Node.js *Learn to do unit testing and to debug your code *Build client-side web applications using React and Redux *Create native mobile applications for Android and iOS with React Native *Write desktop applications with Electron Who this book is for This book is for developers who want to explore the latest JavaScript features, frameworks, and tools for building complete mobile, desktop and web apps, including server and client-side code. You are expected to have working knowledge of JavaScript to get the most out of this book.

A concise walk-through of CentOS 7, starting from installation to securing it’s environment. Key Features *No previous Linux environment experience needed for reading this book *Get comfortable with a popular and stable Red Hat Enterprise Linux distribution *Most of the command line based concepts are explained with graphics Book Description Linux kernel development has been the worlds largest collaborative project to date. With this practical guide, you will learn Linux through one of its most popular and stable distributions. This book will introduce you to essential Linux skills using CentOS 7. It describes how a Linux system is organized, and will introduce you to key command-line concepts you can practice on your own. It will guide you in performing basic system administration tasks and day-to-day operations in a Linux environment. You will learn core system administration skills for managing a system running CentOS 7 or a similar operating system, such as RHEL 7, Scientific Linux, and Oracle Linux. You will be able to perform installation, establish network connectivity and user and process management, modify file permissions, manage text files using the command line, and implement basic security administration after covering this book. By the end of this book, you will have a solid understanding of working with Linux using the command line. What you will learn *Understand file system hierarchy and essential command-line skills *Use Vi editor, I/O redirections and how to work with common text manipulating tools *Create, delete, modify user accounts and manage passwords and their aging policy *Manage file ownership, permissions, and ACL *Execute process management and monitoring on the command line *Validate and manage network configuration using nmcli *Manage remote logins using SSH and file transfer using SCP and Rsync *Understand system logging, how to control system services with systemd and systemctl, and manage firewalId Who this book is for Any individual who wants to learn how to use Linux as server or desktop in his environment. Whether you are a developer, budding system administrator, or tech lover with no previous Linux administration background, you will be able to start your journey in Linux using CentOS 7 with this book.

Explore the best tools and techniques to create lightweight, maintainable, and scalable Python web services Key Features *Combine Python with different data sources to build complex RESTful APIs from scratch *Configure and fine-tune your APIs using the best tools and techniques available *Use command-line and GUI tools to test CRUD operations performed by RESTful Web Services or APIs Book Description Python is the language of choice for millions of developers worldwide that builds great web services in RESTful architecture. This second edition of Hands-On RESTful Python Web Services will cover the best tools you can use to build engaging web services. This book shows you how to develop RESTful APIs using the most popular Python frameworks and all the necessary stacks with Python, combined with related libraries and tools. You’ll learn to incorporate all new features of Python 3.7, Flask 1.0.2, Django 2.1, Tornado 5.1, and also a new framework, Pyramid. As you advance through the chapters, you will get to grips with each of these frameworks to build various web services, and be shown use cases and best practices covering when to use a particular framework. You’ll then successfully develop RESTful APIs with all frameworks and understand how each framework processes HTTP requests and routes URLs. You’ll also discover best practices for validation, serialization, and deserialization. In the concluding chapters, you will take advantage of specific features available in certain frameworks such as integrated ORMs, built-in authorization and authentication, and work with asynchronous code. At the end of each framework, you will write tests for RESTful APIs and improve code coverage. By the end of the book, you will have gained a deep understanding of the stacks needed to build RESTful web services. What you will learn *Select the most appropriate framework based on requirements *Develop complex RESTful APIs from scratch using Python *Use requests handlers, URL patterns, serialization, and validations *Add authentication, authorization, and interaction with ORMs and databases *Debug, test, and improve RESTful APIs with four frameworks *Design RESTful APIs with frameworks and create automated tests Who this book is for This book is for web developers who have a working knowledge of Python and would like to build amazing web services by taking advantage of the various frameworks of Python. You should have some knowledge of RESTful APIs.

Demystify the complexity of machine learning techniques and create evolving, clever solutions to solve your problems Key Features *Master supervised, unsupervised, and semi-supervised ML algorithms and their implementation *Build deep learning models for object detection, image classification, similarity learning, and more *Build, deploy, and scale end-to-end deep neural network models in a production environment Book Description This Learning Path is your complete guide to quickly getting to grips with popular machine learning algorithms. You'll be introduced to the most widely used algorithms in supervised, unsupervised, and semi-supervised machine learning, and learn how to use them in the best possible manner. Ranging from Bayesian models to the MCMC algorithm to Hidden Markov models, this Learning Path will teach you how to extract features from your dataset and perform dimensionality reduction by making use of Python-based libraries. You'll bring the use of TensorFlow and Keras to build deep learning models, using concepts such as transfer learning, generative adversarial networks, and deep reinforcement learning. Next, you'll learn the advanced features of TensorFlow1.x, such as distributed TensorFlow with TF clusters, deploy production models with TensorFlow Serving. You'll implement different techniques related to object classification, object detection, image segmentation, and more. By the end of this Learning Path, you'll have obtained in-depth knowledge of TensorFlow, making you the go-to person for solving artificial intelligence problems This Learning Path includes content from the following Packt products: *Mastering Machine Learning Algorithms by Giuseppe Bonaccorso *Mastering TensorFlow 1.x by Armando Fandango *Deep Learning for Computer Vision by Rajalingappaa Shanmugamani What you will learn *Explore how an ML model can be trained, optimized, and evaluated *Work with Autoencoders and Generative Adversarial Networks *Explore the most important Reinforcement Learning techniques *Build end-to-end deep learning (CNN, RNN, and Autoencoders) models Who this book is for This Learning Path is for data scientists, machine learning engineers, artificial intelligence engineers who want to delve into complex machine learning algorithms, calibrate models, and improve the predictions of the trained model. You will encounter the advanced intricacies and complex use cases of deep learning and AI. A basic knowledge of programming in Python and some understanding of machine learning concepts are required to get the best out of this Learning Path.

Create end-to-end systems that can power robots with artificial vision and deep learning techniques Key Features * Study ROS, the main development framework for robotics, in detail * Learn all about convolutional neural networks, recurrent neural networks, and robotics * Create a chatbot to interact with the robot Book Description Artificial Vision and Language Processing for Robotics begins by discussing the theory behind robots. You'll compare different methods used to work with robots and explore computer vision, its algorithms, and limits. You'll then learn how to control the robot with natural language processing commands. You'll study Word2Vec and GloVe embedding techniques, non-numeric data, recurrent neural network (RNNs), and their advanced models. You'll create a simple Word2Vec model with Keras, as well as build a convolutional neural network (CNN) and improve it with data augmentation and transfer learning. You'll study the ROS and build a conversational agent to manage your robot. You'll also integrate your agent with the ROS and convert an image to text and text to speech. You'll learn to build an object recognition system using a video. By the end of this book, you'll have the skills you need to build a functional application that can integrate with a ROS to extract useful information about your environment. What you will learn * Explore the ROS and build a basic robotic system * Understand the architecture of neural networks * Identify conversation intents with NLP techniques * Learn and use the embedding with Word2Vec and GloVe * Build a basic CNN and improve it using generative models * Use deep learning to implement artificial intelligence(AI)and object recognition * Develop a simple object recognition system using CNNs * Integrate AI with ROS to enable your robot to recognize objects Who this book is for Artificial Vision and Language Processing for Robotics is for robotics engineers who want to learn how to integrate computer vision and deep learning techniques to create complete robotic systems. It will prove beneficial to you if you have working knowledge of Python and a background in deep learning. Knowledge of the ROS is a plus.

Work with the powerful subscription software, Office 365 to increase your organization's efficiency by managing file sharing, email exchange and much more. Key Features * Become well versed with Office 365 and leverage its capabilities for your business * Speed up your workflow and effectively collaborate using Office Web Apps * Learn to set audio and web conferences and seamlessly access your workspace Book Description Microsoft Office 365 combines the popular Office suite with next-generation cloud computing capabilities. With this user guide, you'll be able to implement its software features for effective business communication and collaboration. This book begins by providing you with a quick introduction to the user interface (UI) and the most commonly used features of Office 365. After covering the core aspects of this suite, you'll learn how to perform various email functions via Exchange. Next, you will learn how to communicate using Skype for Business and Microsoft Teams. To boost your productivity, this book will help you learn everything from using instant messaging to conducting audio and web conferences, and even accessing business information from any location. In the final chapters, you will learn to work in a systematic style using file management and collaboration with OneDrive for Business using SharePoint. By the end of this book, you'll be equipped with the knowledge you need to take full advantage of Office 365 and level up your organization's productivity. What you will learn * Understand the UI of Office 365 * Perform a variety of email functions through Exchange * Communicate using Skype for Business and Microsoft Teams * Explore file management using OneDrive for Business * Collaborate using SharePoint * Understand how to leverage Office 365 in your daily tasks Who this book is for If you are an IT professional who wants to upgrade your traditional Office suite, this book is for you. Users looking to learn, configure, manage, and maintain an Office 365 environment in their organization will also find this book useful. Some understanding of Microsoft Office Suite and cloud computing basics will be beneficial.

Discover the power of functional programming, lazy evaluation, monads, concurrency, and immutability to create succinct and expressive implementations Key Features * Get a solid understanding of how to apply functional programming concepts in TypeScript * Explore TypeScript runtime features such as event loop, closures, and Prototypes * Gain deeper knowledge on the pros and cons of TypeScript Book Description Functional programming is a powerful programming paradigm that can help you to write better code. However, learning functional programming can be complicated, and the existing literature is often too complex for beginners. This book is an approachable introduction to functional programming and reactive programming with TypeScript for readers without previous experience in functional programming with JavaScript, TypeScript , or any other programming language. The book will help you understand the pros, cons, and core principles of functional programming in TypeScript. It will explain higher order functions, referential transparency, functional composition, and monads with the help of effective code examples. Using TypeScript as a functional programming language, you’ll also be able to brush up on your knowledge of applying functional programming techniques, including currying, laziness, and immutability, to real-world scenarios. By the end of this book, you will be confident when it comes to using core functional and reactive programming techniques to help you build effective applications with TypeScript. What you will learn * Understand the pros and cons of functional programming * Delve into the principles, patterns, and best practices of functional and reactive programming * Use lazy evaluation to improve the performance of applications * Explore functional optics with Ramda * Gain insights into category theory functional data structures such as Functors and Monads * Use functions as values, so that they can be passed as arguments to other functions Who this book is for This book is designed for readers with no prior experience of functional programming with JavaScript, TypeScript or any other programming language. Some familiarity with TypeScript and web development is a must to grasp the concepts in the book easily.

Apply cloud native patterns and practices to deliver responsive, resilient, elastic, and message-driven systems with confidence Key Features * Discover best practices for applying cloud native patterns to your cloud applications * Explore ways to effectively plan resources and technology stacks for high security and fault tolerance * Gain insight into core architectural principles using real-world examples Book Description Cloud computing has proven to be the most revolutionary IT development since virtualization. Cloud native architectures give you the benefit of more flexibility over legacy systems. This Learning Path teaches you everything you need to know for designing industry-grade cloud applications and efficiently migrating your business to the cloud. It begins by exploring the basic patterns that turn your database inside out to achieve massive scalability. You’ll learn how to develop cloud native architectures using microservices and serverless computing as your design principles. Then, you’ll explore ways to continuously deliver production code by implementing continuous observability in production. In the concluding chapters, you’ll learn about various public cloud architectures ranging from AWS and Azure to the Google Cloud Platform, and understand the future trends and expectations of cloud providers. By the end of this Learning Path, you’ll have learned the techniques to adopt cloud native architectures that meet your business requirements. This Learning Path includes content from the following Packt products: * Cloud Native Development Patterns and Best Practices by John Gilbert * Cloud Native Architectures by Erik Farr et al. What you will learn * Understand the difference between cloud native and traditional architecture * Automate security controls and configuration management * Minimize risk by evolving your monolithic systems into cloud native applications * Explore the aspects of migration, when and why to use it * Apply modern delivery and testing methods to continuously deliver production code * Enable massive scaling by turning your database inside out Who this book is for This Learning Path is designed for developers who want to progress into building cloud native systems and are keen to learn the patterns involved. Software architects, who are keen on designing scalable and highly available cloud native applications, will also find this Learning Path very useful. To easily grasp these concepts, you will need basic knowledge of programming and cloud computing.

Leverage the power of reward-based training for your deep learning models with Python Key Features * Understand Q-learning algorithms to train neural networks using Markov Decision Process (MDP) * Study practical deep reinforcement learning using Q-Networks * Explore state-based unsupervised learning for machine learning models Book Description Q-learning is a machine learning algorithm used to solve optimization problems in artificial intelligence (AI). It is one of the most popular fields of study among AI researchers. This book starts off by introducing you to reinforcement learning and Q-learning, in addition to helping you get familiar with OpenAI Gym as well as libraries such as Keras and TensorFlow. A few chapters into the book, you will gain insights into modelfree Q-learning and use deep Q-networks and double deep Q-networks to solve complex problems. This book will guide you in exploring use cases such as self-driving vehicles and OpenAI Gym’s CartPole problem. You will also learn how to tune and optimize Q-networks and their hyperparameters. As you progress, you will understand the reinforcement learning approach to solving real-world problems. You will also explore how to use Q-learning and related algorithms in real-world applications such as scientific research. Toward the end, you’ll gain a sense of what’s in store for reinforcement learning. By the end of this book, you will be equipped with the skills you need to solve reinforcement learning problems using Q-learning algorithms with OpenAI Gym, Keras, and TensorFlow. What you will learn * Explore the fundamentals of reinforcement learning and the state-action-reward process * Understand Markov decision processes * Get well versed with libraries such as Keras, and TensorFlow * Create and deploy model-free learning and deep Q-learning agents with TensorFlow, Keras, and OpenAI Gym * Choose and optimize a Q-Network’s learning parameters and fine-tune its performance * Discover real-world applications and use cases of Q-learning Who this book is for If you are a machine learning developer, engineer, or professional who wants to delve into the deep learning approach for a complex environment, then this is the book for you. Proficiency in Python programming and basic understanding of decision-making in reinforcement learning is assumed.

Explore the exciting world of machine learning with the fastest growing technology in the world Key Features * Understand various machine learning concepts with real-world examples * Implement a supervised machine learning pipeline from data ingestion to validation * Gain insights into how you can use machine learning in everyday life Book Description Machine learning—the ability of a machine to give right answers based on input data—has revolutionized the way we do business. Applied Supervised Learning with Python provides a rich understanding of how you can apply machine learning techniques in your data science projects using Python. You'll explore Jupyter Notebooks, the technology used commonly in academic and commercial circles with in-line code running support. With the help of fun examples, you'll gain experience working on the Python machine learning toolkit—from performing basic data cleaning and processing to working with a range of regression and classification algorithms. Once you’ve grasped the basics, you'll learn how to build and train your own models using advanced techniques such as decision trees, ensemble modeling, validation, and error metrics. You'll also learn data visualization techniques using powerful Python libraries such as Matplotlib and Seaborn. This book also covers ensemble modeling and random forest classifiers along with other methods for combining results from multiple models, and concludes by delving into cross-validation to test your algorithm and check how well the model works on unseen data. By the end of this book, you'll be equipped to not only work with machine learning algorithms, but also be able to create some of your own! What you will learn * Understand the concept of supervised learning and its applications * Implement common supervised learning algorithms using machine learning Python libraries * Validate models using the k-fold technique * Build your models with decision trees to get results effortlessly * Use ensemble modeling techniques to improve the performance of your model * Apply a variety of metrics to compare machine learning models Who this book is for Applied Supervised Learning with Python is for you if you want to gain a solid understanding of machine learning using Python. It'll help if you to have some experience in any functional or object-oriented language and a basic understanding of Python libraries and expressions, such as arrays and dictionaries.

Explore Qt framework and APIs for building cross-platform applications for mobile devices, embedded systems, and IoT Key Features * Build cross-platform applications and deploy them across mobile and connected devices * Design 2D and 3D UIs for embedded systems using Yocto and Qt Creator * Build machine to machine automation solution using QtSensors, QtMQTT, and QtWebSockets Book Description Qt is a world-class framework, helping you to develop rich graphical user interfaces (GUIs) and multi-platform applications that run on all major desktop platforms and most mobile or embedded platforms. The framework helps you connect the dots across platforms and between online and physical experience. This book will help you leverage the fully-featured Qt framework and its modular cross-platform library classes and intuitive APIs to develop applications for mobile, IoT, and industrial embedded systems. Considerations such as screen size, device orientation changes, and small memory will be discussed. We will focus on various core aspects of embedded and mobile systems, such as connectivity, networking, and sensors; there is no IoT without sensors. You will learn how to quickly design a flexible, fast, and responsive UI that looks great. Going further, you will implement different elements in a matter of minutes and synchronize the UI elements with the 3D assets with high precision. You will learn how to create high-performance embedded systems with 3D/2D user interfaces, and deploy and test on your target hardware. The book will explore several new features, including Qt for WebAssembly. At the end of this book, you will learn about creating a full software stack for embedded Linux systems using Yocto and Boot to Qt for Device Creation. What you will learn * Explore the latest features of Qt, such as preview for Qt for Python and Qt for WebAssembly * Create fluid UIs with a dynamic layout for different sized screens * Deploy embedded applications on Linux systems using Yocto * Design Qt APIs for building applications for embedded and mobile devices * Utilize connectivity for networked and machine automated applications * Discover effective techniques to apply graphical effects using Qt Quick apps Who this book is for The book is ideal for mobile developers, embedded systems engineers and enthusiasts who are interested in building cross-platform applications with Qt. Prior knowledge of C++ is required.

Build efficient and fast Qt applications, target performance problems, and discover solutions to refine your code Key Features * Build efficient and concurrent applications in Qt to create cross-platform applications * Identify performance bottlenecks and apply the correct algorithm to improve application performance * Delve into parallel programming and memory management to optimize your code Book Description Achieving efficient code through performance tuning is one of the key challenges faced by many programmers. This book looks at Qt programming from a performance perspective. You'll explore the performance problems encountered when using the Qt framework and means and ways to resolve them and optimize performance. The book highlights performance improvements and new features released in Qt 5.9, Qt 5.11, and 5.12 (LTE). You'll master general computer performance best practices and tools, which can help you identify the reasons behind low performance, and the most common performance pitfalls experienced when using the Qt framework. In the following chapters, you’ll explore multithreading and asynchronous programming with C++ and Qt and learn the importance and efficient use of data structures. You'll also get the opportunity to work through techniques such as memory management and design guidelines, which are essential to improve application performance. Comprehensive sections that cover all these concepts will prepare you for gaining hands-on experience of some of Qt's most exciting application fields - the mobile and embedded development domains. By the end of this book, you'll be ready to build Qt applications that are more efficient, concurrent, and performance-oriented in nature What you will learn * Understand classic performance best practices * Get to grips with modern hardware architecture and its performance impact * Implement tools and procedures used in performance optimization * Grasp Qt-specific work techniques for graphical user interface (GUI) and platform programming * Make Transmission Control Protocol (TCP) and Hypertext Transfer Protocol (HTTP) performant and use the relevant Qt classes * Discover the improvements Qt 5.9 (and the upcoming versions) holds in store * Explore Qt's graphic engine architecture, strengths, and weaknesses Who this book is for This book is designed for Qt developers who wish to build highly performance applications for desktop and embedded devices. Programming Experience with C++ is required.

Create advanced data and integrated solutions using Azure Event Grid, functions, and containers Key Features * Get familiar with the different design patterns available in Microsoft Azure * Develop Azure cloud architecture and a pipeline management system * Get to know the security best practices for your Azure deployment Book Description Over the years, Azure cloud services have grown quickly, and the number of organizations adopting Azure for their cloud services is also gradually increasing. Leading industry giants are finding that Azure fulfills their extensive cloud requirements. Azure for Architects – Second Edition starts with an extensive introduction to major designing and architectural aspects available with Azure. These design patterns focus on different aspects of the cloud, such as high availability, security, and scalability. Gradually, we move on to other aspects, such as ARM template modular design and deployments. This is the age of microservices and serverless is the preferred implementation mechanism for them. This book covers the entire serverless stack available in Azure including Azure Event Grid, Azure Functions, and Azure Logic Apps. New and advance features like durable functions are discussed at length. A complete integration solution using these serverless technologies is also part of the book. A complete chapter discusses all possible options related to containers in Azure including Azure Kubernetes services, Azure Container Instances and Registry, and Web App for Containers. Data management and integration is an integral part of this book that discusses options for implementing OLTP solutions using Azure SQL, Big Data solutions using Azure Data factory and Data Lake Storage, eventing solutions using stream analytics, and Event Hubs. This book will provide insights into Azure governance features such as tagging, RBAC, cost management, and policies. By the end of this book, you will be able to develop a full-?edged Azure cloud solution that is Enterprise class and future-ready. What you will learn * Create an end-to-end integration solution using Azure Serverless Stack * Learn Big Data solutions and OLTP–based applications on Azure * Understand DevOps implementations using Azure DevOps * Architect solutions comprised of multiple resources in Azure * Develop modular ARM templates * Develop Governance on Azure using locks, RBAC, policies, tags and cost * Learn ways to build data solutions on Azure * Understand the various options related to containers including Azure Kubernetes Services Who this book is for If you are Cloud Architects, DevOps Engineers, or developers who want to learn key architectural aspects of the Azure Cloud platform, then this book is for you. Prior basic knowledge of the Azure Cloud platform is good to have.

Design, develop, and deploy innovative forensic solutions using Python Key Features * Discover how to develop Python scripts for effective digital forensic analysis * Master the skills of parsing complex data structures with Python libraries * Solve forensic challenges through the development of practical Python scripts Book Description Digital forensics plays an integral role in solving complex cybercrimes and helping organizations make sense of cybersecurity incidents. This second edition of Learning Python for Forensics illustrates how Python can be used to support these digital investigations and permits the examiner to automate the parsing of forensic artifacts to spend more time examining actionable data. The second edition of Learning Python for Forensics will illustrate how to develop Python scripts using an iterative design. Further, it demonstrates how to leverage the various built-in and community-sourced forensics scripts and libraries available for Python today. This book will help strengthen your analysis skills and efficiency as you creatively solve real-world problems through instruction-based tutorials. By the end of this book, you will build a collection of Python scripts capable of investigating an array of forensic artifacts and master the skills of extracting metadata and parsing complex data structures into actionable reports. Most importantly, you will have developed a foundation upon which to build as you continue to learn Python and enhance your efficacy as an investigator. What you will learn * Learn how to develop Python scripts to solve complex forensic problems * Build scripts using an iterative design * Design code to accommodate present and future hurdles * Leverage built-in and community-sourced libraries * Understand the best practices in forensic programming * Learn how to transform raw data into customized reports and visualizations * Create forensic frameworks to automate analysis of multiple forensic artifacts * Conduct effective and efficient investigations through programmatic processing Who this book is for If you are a forensics student, hobbyist, or professional seeking to increase your understanding in forensics through the use of a programming language, then Learning Python for Forensics is for you. You are not required to have previous experience in programming to learn and master the content within this book. This material, created by forensic professionals, was written with a unique perspective and understanding for examiners who wish to learn programming.

Master a range of machine learning domains with real-world projects using TensorFlow for R, H2O, MXNet, and more Key Features *Master machine learning, deep learning, and predictive modeling concepts in R 3.5 *Build intelligent end-to-end projects for finance, retail, social media, and a variety of domains *Implement smart cognitive models with helpful tips and best practices Book Description R is one of the most popular languages when it comes to performing computational statistics (statistical computing) easily and exploring the mathematical side of machine learning. With this book, you will leverage the R ecosystem to build efficient machine learning applications that carry out intelligent tasks within your organization. This book will help you test your knowledge and skills, guiding you on how to build easily through to complex machine learning projects. You will first learn how to build powerful machine learning models with ensembles to predict employee attrition. Next, you’ll implement a joke recommendation engine and learn how to perform sentiment analysis on Amazon reviews. You’ll also explore different clustering techniques to segment customers using wholesale data. In addition to this, the book will get you acquainted with credit card fraud detection using autoencoders, and reinforcement learning to make predictions and win on a casino slot machine. By the end of the book, you will be equipped to confidently perform complex tasks to build research and commercial projects for automated operations. What you will learn *Explore deep neural networks and various frameworks that can be used in R *Develop a joke recommendation engine to recommend jokes that match users’ tastes *Create powerful ML models with ensembles to predict employee attrition *Build autoencoders for credit card fraud detection *Work with image recognition and convolutional neural networks *Make predictions for casino slot machine using reinforcement learning *Implement NLP techniques for sentiment analysis and customer segmentation Who this book is for If you’re a data analyst, data scientist, or machine learning developer who wants to master machine learning concepts using R by building real-world projects, this is the book for you. Each project will help you test your skills in implementing machine learning algorithms and techniques. A basic understanding of machine learning and working knowledge of R programming is necessary to get the most out of this book.

Understand and solve complex computational problems and write efficient code with Kotlin Key Features * Learn about important data structures such as lists, arrays, queues, and stacks * Design custom algorithms for real-life implementations * Identify suitable tools for different scenarios and deliver immediate results Book Description Data structures and algorithms are more than just theoretical concepts. They help you become familiar with computational methods for solving problems and writing logical code. Equipped with this knowledge, you can write efficient programs that run faster and use less memory. Hands-On Data Structures and Algorithms with Kotlin book starts with the basics of algorithms and data structures, helping you get to grips with the fundamentals and measure complexity. You'll then move on to exploring the basics of functional programming while getting used to thinking recursively. Packed with plenty of examples along the way, this book will help you grasp each concept easily. In addition to this, you'll get a clear understanding of how the data structures in Kotlin's collection framework work internally. By the end of this book, you will be able to apply the theory of data structures and algorithms to work out real-world problems. What you will learn * Understand the basic principles of algorithms and data structures * Explore general-purpose data structures with arrays and linked lists * Get to grips with the basics of stacks, queues, and double-ended queues * Understand functional programming and related data structures * Use performant searching and efficient sorting * Uncover how Kotlin's collection framework functions * Become adept at implementing different types of maps Who this book is for If you're a Kotlin developer who wants to learn the intricacies of implementing data structures and algorithms for scalable application development, this book is for you.

Push the limits of what C - and you - can do, with this high-intensity guide to the most advanced capabilities of C Key Features * Make the most of C’s low-level control, flexibility, and high performance * A comprehensive guide to C’s most powerful and challenging features * A thought-provoking guide packed with hands-on exercises and examples Book Description There’s a lot more to C than knowing the language syntax. The industry looks for developers with a rigorous, scientific understanding of the principles and practices. Extreme C will teach you to use C’s advanced low-level power to write effective, efficient systems. This intensive, practical guide will help you become an expert C programmer. Building on your existing C knowledge, you will master preprocessor directives, macros, conditional compilation, pointers, and much more. You will gain new insight into algorithm design, functions, and structures. You will discover how C helps you squeeze maximum performance out of critical, resource-constrained applications. C still plays a critical role in 21st-century programming, remaining the core language for precision engineering, aviations, space research, and more. This book shows how C works with Unix, how to implement OO principles in C, and fully covers multi-processing. In Extreme C, Amini encourages you to think, question, apply, and experiment for yourself. The book is essential for anybody who wants to take their C to the next level. What you will learn * Build advanced C knowledge on strong foundations, rooted in first principles * Understand memory structures and compilation pipeline and how they work, and how to make most out of them * Apply object-oriented design principles to your procedural C code * Write low-level code that’s close to the hardware and squeezes maximum performance out of a computer system * Master concurrency, multithreading, multi-processing, and integration with other languages * Unit Testing and debugging, build systems, and inter-process communication for C programming Who this book is for Extreme C is for C programmers who want to dig deep into the language and its capabilities. It will help you make the most of the low-level control C gives you.

Implement reinforcement learning techniques and algorithms with the help of real-world examples and recipes Key Features * Use PyTorch 1.x to design and build self-learning artificial intelligence (AI) models * Implement RL algorithms to solve control and optimization challenges faced by data scientists today * Apply modern RL libraries to simulate a controlled environment for your projects Book Description Reinforcement learning (RL) is a branch of machine learning that has gained popularity in recent times. It allows you to train AI models that learn from their own actions and optimize their behavior. PyTorch has also emerged as the preferred tool for training RL models because of its efficiency and ease of use. With this book, you'll explore the important RL concepts and the implementation of algorithms in PyTorch 1.x. The recipes in the book, along with real-world examples, will help you master various RL techniques, such as dynamic programming, Monte Carlo simulations, temporal difference, and Q-learning. You'll also gain insights into industry-specific applications of these techniques. Later chapters will guide you through solving problems such as the multi-armed bandit problem and the cartpole problem using the multi-armed bandit algorithm and function approximation. You'll also learn how to use Deep Q-Networks to complete Atari games, along with how to effectively implement policy gradients. Finally, you'll discover how RL techniques are applied to Blackjack, Gridworld environments, internet advertising, and the Flappy Bird game. By the end of this book, you'll have developed the skills you need to implement popular RL algorithms and use RL techniques to solve real-world problems. What you will learn * Use Q-learning and the state–action–reward–state–action (SARSA) algorithm to solve various Gridworld problems * Develop a multi-armed bandit algorithm to optimize display advertising * Scale up learning and control processes using Deep Q-Networks * Simulate Markov Decision Processes, OpenAI Gym environments, and other common control problems * Select and build RL models, evaluate their performance, and optimize and deploy them * Use policy gradient methods to solve continuous RL problems Who this book is for Machine learning engineers, data scientists and AI researchers looking for quick solutions to different reinforcement learning problems will find this book useful. Although prior knowledge of machine learning concepts is required, experience with PyTorch will be useful but not necessary.

Cut through the noise and get real results with a step-by-step approach to learning Java programming Key Features * Ideal for the Java beginner who is getting started for the first time * A step-by-step Java tutorial with exercises and activities that help build key skills * Structured to let you progress at your own pace, on your own terms * Use your physical copy to redeem free access to the online interactive edition Book Description You already know you want to learn Java, and a smarter way to learn Java 12 is to learn by doing. The Java Workshop focuses on building up your practical skills so that you can develop high-performance Java applications that work flawlessly within the JVM across web, mobile and desktop. You'll learn from real examples that lead to real results. Throughout The Java Workshop, you'll take an engaging step-by-step approach to understanding Java. You won't have to sit through any unnecessary theory. If you're short on time you can jump into a single exercise each day or spend an entire weekend learning about Reactive programming and Unit testing. It's your choice. Learning on your terms, you'll build up and reinforce key skills in a way that feels rewarding. Every physical copy of The Java Workshop unlocks access to the interactive edition. With videos detailing all exercises and activities, you'll always have a guided solution. You can also benchmark yourself against assessments, track progress, and receive free content updates. You'll even earn a secure credential that you can share and verify online upon completion. It's a premium learning experience that's included with your printed copy. To redeem, follow the instructions located at the start of your Java book. Fast-paced and direct, The Java Workshop is the ideal companion for Java beginners. You'll build and iterate on your code like a software developer, learning along the way. This process means that you'll find that your new skills stick, embedded as best practice. A solid foundation for the years ahead. What you will learn * Get to grips with fundamental concepts and conventions of Java 12 * Write clean and well-commented code that's easy to maintain * Debug and compile logical errors and handle exceptions in your programs * Understand how to work with Java APIs and Java streams * Learn how to use third-party libraries and software development kits (SDKs) * Discover how you can work with information stored in databases * Understand how you can keep data secure with cryptography and encryption * Learn how to keep your development process bug-free with unit testing in Java Who this book is for Our goal at Packt is to help you be successful, in whatever it is you choose to do. The Java Workshop is an ideal Java tutorial for the Java beginner who is just getting started. Pick up a Workshop today, and let Packt help you develop skills that stick with you for life.

Create dynamic dashboards to bring interactive data visualization to your enterprise using Qlik Sense Key Features * Implement various Qlik Sense features to create interactive dashboards * Analyze data easily and make business decisions faster using Qlik Sense * Perform self-service data analytics and geospatial analytics using an example-based approach Book Description Qlik Sense allows you to explore simple-to-complex data to reveal hidden insights and data relationships to make business-driven decisions. Hands-On Business Intelligence with Qlik Sense begins by helping you get to grips with underlying Qlik concepts and gives you an overview of all Qlik Sense’s features. You will learn advanced modeling techniques and learn how to analyze the data loaded using a variety of visualization objects. You’ll also be trained on how to share apps through Qlik Sense Enterprise and Qlik Sense Cloud and how to perform aggregation with AGGR. As you progress through the chapters, you’ll explore the stories feature to create data-driven presentations and update an existing story. This book will guide you through the GeoAnalytics feature with the geo-mapping object and GeoAnalytics connector. Furthermore, you’ll learn about the self-service analytics features and perform data forecasting using advanced analytics. Lastly, you’ll deploy Qlik Sense apps for mobile and tablet. By the end of this book, you will be well-equipped to run successful business intelligence applications using Qlik Sense's functionality, data modeling techniques, and visualization best practices. What you will learn * Discover how to load, reshape, and model data for analysis * Apply data visualization practices to create stunning dashboards * Make use of Python and R for advanced analytics * Perform geo-analysis to create visualizations using native objects * Learn how to work with AGGR and data stories Who this book is for If you’re a data analyst, BI developer, or interested in business intelligence and want to gain practical experience of working on Qlik Sense, this book is for you. You’ll also find it useful if you want to explore Qlik Sense’s next-generation applications for self-service business intelligence. No prior experience of working with Qlik Sense is required.